def test_18_filter_reads(self):
if CHKTIME:
t0 = time()
for ali in ['map', 'sam']:
seed(1)
if 13436 == int(random()*100000):
same_seed = True
genome = generate_random_ali(ali)
genome_bis = parse_fasta('test.fa~', verbose=False)
self.assertEqual(genome, genome_bis)
else:
same_seed = False
genome = parse_fasta('test.fa~')
# PARSE SAM
if ali == 'map':
from pytadbit.parsers.map_parser import parse_map as parser
else:
try:
from pytadbit.parsers.sam_parser import parse_sam as parser
except ImportError:
print 'ERROR: PYSAM not found, skipping test\n'
continue
parser(['test_read1.%s~' % (ali)], ['test_read2.%s~' % (ali)],
'./lala1-%s~' % (ali), './lala2-%s~' % (ali), genome,
re_name='DPNII', mapper='GEM')
# GET INTERSECTION
from pytadbit.mapping.mapper import get_intersection
get_intersection('lala1-%s~' % (ali), 'lala2-%s~' % (ali),
'lala-%s~' % (ali))
# FILTER
masked = filter_reads('lala-%s~' % (ali), verbose=False,
fast=(ali=='map'))
self.assertEqual(masked[1]['reads'], 1000)
self.assertEqual(masked[2]['reads'], 1000)
self.assertEqual(masked[3]['reads'], 1000)
self.assertEqual(masked[4]['reads'], 1000)
if same_seed:
self.assertEqual(masked[5]['reads'], 1125)
self.assertEqual(masked[6]['reads'], 2328)
self.assertEqual(masked[7]['reads'], 0)
self.assertEqual(masked[8]['reads'], 94)
self.assertEqual(masked[10]['reads'], 1)
else:
self.assertTrue (masked[5]['reads'] > 1000)
self.assertEqual(masked[9]['reads'], 1000)
apply_filter('lala-map~', 'lala-map-filt~', masked, filters=[1],
reverse=True, verbose=False)
self.assertEqual(len([True for l in open('lala-map-filt~')
if not l.startswith('#')]), 1000)
d = plot_iterative_mapping('lala1-map~', 'lala2-map~')
self.assertEqual(d[0][1], 6000)
if CHKTIME:
self.assertEqual(True, True)
print '18', time() - t0
def main():
fastq = '/scratch/db/FASTQs/hsap/dixon_2012/dixon-2012_200bp.fastq'
fastq = 'short_dixon-2012_200bp.fastq'
# fastq = '/scratch/test/sample_dataset/FASTQs/sample_hsap_HindIII.fastq'
gem_index_path = '/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.gem'
out_map_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read1/'
out_map_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read2/'
temp_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp1/'
temp_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp2/'
print 'read 1'
outfiles1 = full_mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
temp_dir=temp_dir1, windows=((1,100),), add_site=True)
print 'read 2'
outfiles2 = full_mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
temp_dir=temp_dir2, windows=((101, 200),), add_site=True)
# print 'read 1'
# outfiles1 = mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
# temp_dir=temp_dir1,
# windows=(zip(*([0] * len(range(25, 105, 5)),
# range(25,105,5)))))
# print 'read 2'
# outfiles2 = mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
# temp_dir=temp_dir2,
# windows=(zip(*([100] * len(range(125, 205, 5)),
# range(125,205,5)))))
print outfiles1
print 'xcmvnkljnv'
print outfiles2
from pytadbit.parsers.map_parser import parse_map
from pytadbit.parsers.genome_parser import parse_fasta
from pytadbit.mapping.mapper import get_intersection
from pytadbit.mapping.filter import filter_reads, apply_filter
read1, read2 = 'read1.tsv', 'read2.tsv',
parse_map(outfiles1, outfiles2, out_file1=read1, out_file2=read2,
genome_seq=parse_fasta('/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.fa'),
re_name='HindIII', verbose=True)
reads = 'both_reads.tsv'
get_intersection(read1, read2, reads)
masked = filter_reads(reads)
freads = 'filtered_reads.tsv'
apply_filter(reads, freads, masked)
def main():
fastq = '/scratch/db/FASTQs/hsap/dixon_2012/dixon-2012_200bp.fastq'
fastq = 'short_dixon-2012_200bp.fastq'
# fastq = '/scratch/test/sample_dataset/FASTQs/sample_hsap_HindIII.fastq'
gem_index_path = '/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.gem'
out_map_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read1/'
out_map_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/read2/'
temp_dir1 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp1/'
temp_dir2 = '/home/fransua/Box/tadbits/tadbit/_pytadbit/mapping/tmp2/'
print 'read 1'
outfiles1 = full_mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
temp_dir=temp_dir1, windows=((1,100),), add_site=True)
print 'read 2'
outfiles2 = full_mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
temp_dir=temp_dir2, windows=((101, 200),), add_site=True)
# print 'read 1'
# outfiles1 = mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
# temp_dir=temp_dir1,
# windows=(zip(*([0] * len(range(25, 105, 5)),
# range(25,105,5)))))
# print 'read 2'
# outfiles2 = mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
# temp_dir=temp_dir2,
# windows=(zip(*([100] * len(range(125, 205, 5)),
# range(125,205,5)))))
print outfiles1
print 'xcmvnkljnv'
print outfiles2
from pytadbit.parsers.map_parser import parse_map
from pytadbit.parsers.genome_parser import parse_fasta
from pytadbit.mapping.mapper import get_intersection
from pytadbit.mapping.filter import filter_reads, apply_filter
read1, read2 = 'read1.tsv', 'read2.tsv',
parse_map(outfiles1, outfiles2, out_file1=read1, out_file2=read2,
genome_seq=parse_fasta('/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.fa'),
re_name='HindIII', verbose=True)
reads = 'both_reads.tsv'
get_intersection(read1, read2, reads)
masked = filter_reads(reads)
freads = 'filtered_reads.tsv'
apply_filter(reads, freads, masked)
}
out1.write(read.format(**read1))
out2.write(read.format(**read2))
i += 1
out1.close()
out2.close()
# PARSE SAM
if ali == 'map':
from pytadbit.parsers.map_parser import parse_map as parser
else:
from pytadbit.parsers.sam_parser import parse_sam as parser
parser(['test_read1.%s~' % (ali)], ['test_read2.%s~' % (ali)],
'./lala1-%s~' % (ali),
'./lala2-%s~' % (ali),
genome,
re_name='DPNII',
mapper='GEM')
# GET INTERSECTION
from pytadbit.mapping.mapper import get_intersection
get_intersection('lala1-%s~' % (ali), 'lala2-%s~' % (ali), 'lala-%s~' % (ali))
# FILTER
from pytadbit.mapping.filter import filter_reads
masked = filter_reads('lala-%s~' % (ali))
else:
read2 = {'crm': crm1, 'pos': pos1, 'flag': flags[sd1], 'id': 'lala05.1%011d' % (i)}
read1 = {'crm': crm2, 'pos': pos2, 'flag': flags[sd2], 'id': 'lala05.1%011d' % (i)}
out1.write(read.format(**read1))
out2.write(read.format(**read2))
i += 1
out1.close()
out2.close()
# PARSE SAM
if ali == 'map':
from pytadbit.parsers.map_parser import parse_map as parser
else:
from pytadbit.parsers.sam_parser import parse_sam as parser
parser(['test_read1.%s~' % (ali)], ['test_read2.%s~' % (ali)],
'./lala1-%s~' % (ali), './lala2-%s~' % (ali), genome,
re_name='DPNII', mapper='GEM')
# GET INTERSECTION
from pytadbit.mapping.mapper import get_intersection
get_intersection('lala1-%s~' % (ali), 'lala2-%s~' % (ali), 'lala-%s~' % (ali))
# FILTER
from pytadbit.mapping.filter import filter_reads
masked = filter_reads('lala-%s~' % (ali))
def make_matrices(left_reads_fastq, right_reads_fastq, reads_fastq, genome_fasta, genome_index, \
output_directory, output_prefix, enzyme, res, chromosomes, threads_number, \
clean_tmp, tmp_dir):
print 'Begin to process reads.'
left_reads = ''
right_reads = ''
if reads_fastq != '': # left and right reads are stored in one file
range_start_left, range_stop_left, \
range_start_right, range_stop_right = calc_left_right_ranges(reads_fastq)
print 'Reads: ', reads_fastq
left_reads = reads_fastq
right_reads = reads_fastq
else: # left and right reads are stored separately
range_start_left, range_stop_left, \
range_start_right, range_stop_right = calc_range(left_reads_fastq)
print 'Left reads: ', left_reads_fastq
print 'Right reads: ', right_reads_fastq
print 'Output prefix: ', output_prefix
left_reads = left_reads_fastq
right_reads = right_reads_fastq
print 'Reference genome FASTA: ', genome_fasta
print 'Reference genome GEM index:', genome_index
print 'Output directory: ', output_directory
print 'Temp directory: ', tmp_dir
print 'Enzyme: ', enzyme
print 'Resolution: ', res, 'bp'
print 'Number of threads: ', threads_number
print 'Start pos for left reads: ', range_start_left
print 'Stop pos for left reads: ', range_stop_left
print 'Start pos for right reads: ', range_start_right
print 'Stop pos for right reads: ', range_stop_right
stdout.flush()
# map left reads to reference genome
out_sam_left_name = splitext(basename(left_reads))[0] + '_left.sam'
out_sam_left_path = join(output_directory, out_sam_left_name)
print 'Iterative mapping of left reads (using ' + str(threads_number) + ' threads)...'
stdout.flush()
sams_left = iterative_mapping(genome_index, left_reads, out_sam_left_path, \
range_start_left, range_stop_left, nthreads=threads_number,
temp_dir=tmp_dir)
print 'Done.'
stdout.flush()
# map right reads to reference genome
out_sam_right_name = splitext(basename(right_reads))[0] + '_right.sam'
out_sam_right_path = join(output_directory, out_sam_right_name)
print 'Iterative mapping of right reads (using ' + str(threads_number) + ' threads)...'
stdout.flush()
sams_right = iterative_mapping(genome_index, right_reads, out_sam_right_path, \
range_start_right, range_stop_right, nthreads=threads_number,
temp_dir=tmp_dir)
print 'Done.'
stdout.flush()
# load reference genome sequence
print 'Load reference genome sequence...'
stdout.flush()
chroms = chromosomes[:]
genome_seq = parse_fasta(genome_fasta, chr_names=chroms)
print 'Done.'
stdout.flush()
# create files with information about every left and right read
# and about their placement with respect to restriction sites
tsv_left_name = splitext(basename(left_reads))[0] + '_left.tsv'
tsv_left = join(output_directory, tsv_left_name)
tsv_right_name = splitext(basename(right_reads))[0] + '_right.tsv'
tsv_right = join(output_directory, tsv_right_name)
print 'Get information about restriction sites and reads placement...'
stdout.flush()
parse_sam(sams_left, sams_right, tsv_left, tsv_right, genome_seq, enzyme, \
verbose=True, ncpus=8)
print 'Done.'
stdout.flush()
# create file with both left and right reads that uniquelly mapped to reference genome
if reads_fastq != '': # left and right reads are stored in one file
common_reads_prefix = splitext(basename(reads_fastq))[0]
else: # left and right reads are stored separately
common_reads_prefix = output_prefix
uniq_reads_name = common_reads_prefix + '_both_map_uniq.tsv'
uniq_reads = join(output_directory, uniq_reads_name)
print 'Merge info about left and right reads in one file...'
stdout.flush()
get_intersection(tsv_left, tsv_right, uniq_reads, verbose=True)
print 'Done.'
stdout.flush()
# find read IDs that are filtered by default TADbit filters
print 'Mask reads...'
stdout.flush()
# debug
print "uniq_reads =", uniq_reads
masked = filter_reads(uniq_reads)
print 'Done.'
stdout.flush()
# apply all filters (exclude reads that were filtered)
print 'Filter masked reads...'
stdout.flush()
filtered_reads_name = common_reads_prefix + '_filtered.tsv'
filtered_reads = join(output_directory, filtered_reads_name)
apply_filter(uniq_reads, filtered_reads, masked)
print 'Done.'
stdout.flush()
# create matrices (one matrix per chromosome)
print 'Create Hi-C maps (one per chromosome)...'
stdout.flush()
hic_map(filtered_reads, resolution=res, by_chrom='intra', savedata=output_directory)
print 'Done.'
stdout.flush()
print 'Add resolution (' + str(resolution) + ') to matrix filenames...'
stdout.flush()
add_resolution(chromosomes, resolution, output_directory)
print 'Done.'
stdout.flush()
print 'Add headers to matrix files...'
stdout.flush()
add_headers(chromosomes, resolution, output_directory)
print 'Done.'
stdout.flush()
if clean_tmp: # Remove all SAM and TSV files from the output directory
print 'Remove SAM and TSV files from the output directory.'
stdout.flush()
map(os.remove, glob.glob(out_sam_left_path + '*'))
map(os.remove, glob.glob(out_sam_right_path + '*'))
map(os.remove, glob.glob(join(output_directory, '*.tsv')))
print 'Done.'
stdout.flush()
def test_18_filter_reads(self):
if CHKTIME:
t0 = time()
for ali in ['map', 'sam']:
seed(1)
if 13436 == int(random() * 100000):
same_seed = True
genome = generate_random_ali(ali)
genome_bis = parse_fasta('test.fa~', verbose=False)
self.assertEqual(genome, genome_bis)
else:
same_seed = False
genome = parse_fasta('test.fa~')
# PARSE SAM
if ali == 'map':
from pytadbit.parsers.map_parser import parse_map as parser
else:
try:
from pytadbit.parsers.sam_parser import parse_sam as parser
except ImportError:
print 'ERROR: PYSAM not found, skipping test\n'
continue
parser(['test_read1.%s~' % (ali)], ['test_read2.%s~' % (ali)],
'./lala1-%s~' % (ali),
'./lala2-%s~' % (ali),
genome,
re_name='DPNII',
mapper='GEM')
# GET INTERSECTION
from pytadbit.mapping.mapper import get_intersection
get_intersection('lala1-%s~' % (ali), 'lala2-%s~' % (ali),
'lala-%s~' % (ali))
# FILTER
masked = filter_reads('lala-%s~' % (ali),
verbose=False,
fast=(ali == 'map'))
self.assertEqual(masked[1]['reads'], 1000)
self.assertEqual(masked[2]['reads'], 1000)
self.assertEqual(masked[3]['reads'], 1000)
self.assertEqual(masked[4]['reads'], 1000)
if same_seed:
self.assertEqual(masked[5]['reads'], 1125)
self.assertEqual(masked[6]['reads'], 2328)
self.assertEqual(masked[7]['reads'], 0)
self.assertEqual(masked[8]['reads'], 94)
self.assertEqual(masked[10]['reads'], 1)
else:
self.assertTrue(masked[5]['reads'] > 1000)
self.assertEqual(masked[9]['reads'], 1000)
apply_filter('lala-map~',
'lala-map-filt~',
masked,
filters=[1],
reverse=True)
self.assertEqual(
len([
True for l in open('lala-map-filt~') if not l.startswith('#')
]), 1000)
d = plot_iterative_mapping('lala1-map~', 'lala2-map~')
self.assertEqual(d[0][1], 6000)
if CHKTIME:
self.assertEqual(True, True)
print '18', time() - t0
outfiles1 = full_mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
temp_dir=temp_dir1, frag_map=False,
windows=(zip(*(r_beg1, r_end1))))
print 'read 2'
outfiles2 = full_mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
temp_dir=temp_dir2, frag_map=False,
windows=(zip(*(r_beg2, r_end2))))
parse_thing = parse_map
elif mapper == 3:
print 'read 1'
outfiles1 = full_mapping(gem_index_path, fastq, out_map_dir1, 'HindIII',
temp_dir=temp_dir1,
windows=(zip(*(r_beg1, r_end1))))
print 'read 2'
outfiles2 = full_mapping(gem_index_path, fastq, out_map_dir2, 'HindIII',
temp_dir=temp_dir2,
windows=(zip(*(r_beg2, r_end2))))
parse_thing = parse_map
read1, read2 = 'read1.tsv_%s-%s' % (mapper, win), 'read2.tsv_%s-%s' % (mapper, win)
parse_thing(outfiles1, outfiles2, out_file1=read1, out_file2=read2,
genome_seq=parse_fasta('/scratch/db/index_files/Homo_sapiens-79/Homo_sapiens.fa'),
re_name='HindIII', verbose=True)
reads = 'both_reads.tsv_%s-%s' % (mapper, win)
get_intersection(read1, read2, reads)
masked = filter_reads(reads)
freads = 'filtered_reads.tsv_%s-%s' % (mapper, win)
apply_filter(reads, freads, masked)
# 8, but leave some room for you other applications
max_reads_per_chunk = chunk,
single_end = True)
sams1 = [OUTPATH + fnam for fnam in os.listdir(OUTPATH) if fnam.rsplit('.', 2)[0].endswith('_r1.txt')]
sams2 = [OUTPATH + fnam for fnam in os.listdir(OUTPATH) if fnam.rsplit('.', 2)[0].endswith('_r2.txt')]
print 'created thes SAM files:', sams2
parse_sam(sams1, sams2, frags,
OUTPATH + 'reads1_%s.tsv' % rep, OUTPATH + 'reads2_%s.tsv' % rep,
genome_seq, 'HindIII', verbose=True)
reads1 = OUTPATH + 'reads1_%s.tsv' % rep
reads2 = OUTPATH + 'reads2_%s.tsv' % rep
reads = OUTPATH + 'reads12_%s.tsv' % rep
get_intersection(reads1, reads2, reads, verbose=True)
from pytadbit.mapping.analyze import hic_map
hic_map(reads, genome_seq, resolution=100000, savedata='lala')
from pytadbit.mapping.analyze import plot_genomic_distribution
plot_genomic_distribution(reads, resolution=50000, genome_seq=genome_seq) # because I know it
# 690691 SRR_test_10000000/reads1_SRR_test.tsv
# 690691 SRR_test_100000/reads1_SRR_test.tsv
# 1242927 SRR_test_200000/reads1_SRR_test.tsv
# 1035866 SRR_test_500000/reads1_SRR_test.tsv
def make_matrices(left_reads_fastq, right_reads_fastq, reads_fastq, genome_fasta, genome_index, \
output_directory, output_prefix, enzyme, res, chromosomes, threads_number, \
clean_tmp, tmp_dir):
print 'Begin to process reads.'
left_reads = ''
right_reads = ''
if reads_fastq != '': # left and right reads are stored in one file
range_start_left, range_stop_left, \
range_start_right, range_stop_right = calc_left_right_ranges(reads_fastq)
print 'Reads: ', reads_fastq
left_reads = reads_fastq
right_reads = reads_fastq
else: # left and right reads are stored separately
range_start_left, range_stop_left, \
range_start_right, range_stop_right = calc_range(left_reads_fastq)
print 'Left reads: ', left_reads_fastq
print 'Right reads: ', right_reads_fastq
print 'Output prefix: ', output_prefix
left_reads = left_reads_fastq
right_reads = right_reads_fastq
print 'Reference genome FASTA: ', genome_fasta
print 'Reference genome GEM index:', genome_index
print 'Output directory: ', output_directory
print 'Temp directory: ', tmp_dir
print 'Enzyme: ', enzyme
print 'Resolution: ', res, 'bp'
print 'Number of threads: ', threads_number
print 'Start pos for left reads: ', range_start_left
print 'Stop pos for left reads: ', range_stop_left
print 'Start pos for right reads: ', range_start_right
print 'Stop pos for right reads: ', range_stop_right
stdout.flush()
# map left reads to reference genome
out_sam_left_name = splitext(basename(left_reads))[0] + '_left.sam'
out_sam_left_path = join(output_directory, out_sam_left_name)
print 'Iterative mapping of left reads (using ' + str(
threads_number) + ' threads)...'
stdout.flush()
sams_left = iterative_mapping(genome_index, left_reads, out_sam_left_path, \
range_start_left, range_stop_left, nthreads=threads_number,
temp_dir=tmp_dir)
print 'Done.'
stdout.flush()
# map right reads to reference genome
out_sam_right_name = splitext(basename(right_reads))[0] + '_right.sam'
out_sam_right_path = join(output_directory, out_sam_right_name)
print 'Iterative mapping of right reads (using ' + str(
threads_number) + ' threads)...'
stdout.flush()
sams_right = iterative_mapping(genome_index, right_reads, out_sam_right_path, \
range_start_right, range_stop_right, nthreads=threads_number,
temp_dir=tmp_dir)
print 'Done.'
stdout.flush()
# load reference genome sequence
print 'Load reference genome sequence...'
stdout.flush()
chroms = chromosomes[:]
genome_seq = parse_fasta(genome_fasta, chr_names=chroms)
print 'Done.'
stdout.flush()
# create files with information about every left and right read
# and about their placement with respect to restriction sites
tsv_left_name = splitext(basename(left_reads))[0] + '_left.tsv'
tsv_left = join(output_directory, tsv_left_name)
tsv_right_name = splitext(basename(right_reads))[0] + '_right.tsv'
tsv_right = join(output_directory, tsv_right_name)
print 'Get information about restriction sites and reads placement...'
stdout.flush()
parse_sam(sams_left, sams_right, tsv_left, tsv_right, genome_seq, enzyme, \
verbose=True, ncpus=8)
print 'Done.'
stdout.flush()
# create file with both left and right reads that uniquelly mapped to reference genome
if reads_fastq != '': # left and right reads are stored in one file
common_reads_prefix = splitext(basename(reads_fastq))[0]
else: # left and right reads are stored separately
common_reads_prefix = output_prefix
uniq_reads_name = common_reads_prefix + '_both_map_uniq.tsv'
uniq_reads = join(output_directory, uniq_reads_name)
print 'Merge info about left and right reads in one file...'
stdout.flush()
get_intersection(tsv_left, tsv_right, uniq_reads, verbose=True)
print 'Done.'
stdout.flush()
# find read IDs that are filtered by default TADbit filters
print 'Mask reads...'
stdout.flush()
masked = filter_reads(uniq_reads)
print 'Done.'
stdout.flush()
# apply all filters (exclude reads that were filtered)
print 'Filter masked reads...'
stdout.flush()
filtered_reads_name = common_reads_prefix + '_filtered.tsv'
filtered_reads = join(output_directory, filtered_reads_name)
apply_filter(uniq_reads, filtered_reads, masked)
print 'Done.'
stdout.flush()
# create matrices (one matrix per chromosome)
print 'Create Hi-C maps (one per chromosome)...'
stdout.flush()
hic_map(filtered_reads,
resolution=res,
by_chrom='intra',
savedata=output_directory)
print 'Done.'
stdout.flush()
print 'Add resolution (' + str(resolution) + ') to matrix filenames...'
stdout.flush()
add_resolution(chromosomes, resolution, output_directory)
print 'Done.'
stdout.flush()
print 'Add headers to matrix files...'
stdout.flush()
add_headers(chromosomes, resolution, output_directory)
print 'Done.'
stdout.flush()
if clean_tmp: # Remove all SAM and TSV files from the output directory
print 'Remove SAM and TSV files from the output directory.'
stdout.flush()
remove(out_sam_left_path + '*')
remove(out_sam_right_path + '*')
remove(join(output_directory, '*.tsv'))
print 'Done.'
stdout.flush()
break
read1 = {'crm': crm, 'pos': pos1, 'flag': sd1, 'id': 'lala04.%012d' % (i)}
read2 = {'crm': crm, 'pos': pos2, 'flag': sd2, 'id': 'lala04.%012d' % (i)}
out1.write(read_str.format(**read1))
out2.write(read_str.format(**read2))
# TOO CLOSE FROM RE
out1.close()
out2.close()
# PARSE SAM
from pytadbit.parsers.sam_parser import parse_sam
parse_sam(['test_read1.sam~'], ['test_read2.sam~'],
'lala1~', 'lala2~', genome, re_name='DPNII', mapper='GEM')
# GET INTERSECTION
from pytadbit.mapping.mapper import get_intersection
get_intersection('lala1~', 'lala2~', 'lala~')
# FILTER
from pytadbit.mapping.filter import filter_reads
masked = filter_reads('lala~')
